In recent years, a video surveillance system is being widespread which is used for the purpose of preventing crimes and identifying a criminal in a case a crime took place. In the video surveillance system, it is difficult to visually retrieve a target person, and the like, from a large amount of recorded moving image, and thus realization of a mechanical retrieval mechanism is desired.
An example of such system is described in PTL 1. In the system described in PTL 1, a “feature quantity” extracted from a face, a color, and the like in the image is used. The feature quantity is a multi-dimensional vector, and a similarity between the feature quantities can be calculated through a method described in PTL 2, and the like.
In the system described in the above-described literature, the feature quantity is extracted from each frame image of the moving image of the surveillance camera, and then saved in a database. When retrieving from the moving image of the surveillance camera, the feature quantity is extracted from the image including the content desired to be retrieved. The similarity between such feature quantity and the feature quantity in the database is calculated, and the image corresponding to the feature quantity having the highest similarity is outputted to allow the retrieval of the moving image.
It is an expensive process to search for the feature quantity having the highest similarity with the feature quantity desired which is retrieved from a large amount of feature quantity in the database. In PTL 1, the cost of retrieval is reduced by degenerating the dimensions of the vector of the feature quantity, and carrying out the process which is approximate to a low dimension.
An image retrieving device described in PTL 3 is a device that retrieves a similar image, and when a face is detected from the video, the device computes a feature quantity of the detected face image and stores the computed feature quantity in an image feature quantity storage unit with a registration ID, a camera ID, a time, a reduced image data, and an image storage location. PTL 3 describes using the image feature quantity stored in the image feature quantity storage unit to retrieve a similar image, and then determining that the similarity is high when the similarity is greater than or equal to a predetermined threshold value. The registration ID or the image ID of the image determined to have high similarity is also temporarily stored with the similarity.